New LMI conditions for global exponential stability of cellular neural networks with delays

In this paper, we investigate further cellular neural networks model with delays. We allow the model to have nondifferentiable and unbounded signal function, and use linear matrix inequality (LMI) framework and Homeomorphism theorem to prove the existence and uniqueness of the equilibrium, and derive some new sufficient condition ensuring global exponential stability of the networks. Two examples with their numerical simulations are provided to show the correctness of our analysis. It is believed that these results are significant and useful for the design and applications of cellular neural networks.